APierrot/clr: Curve Linear Regression via Dimension Reduction
A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) <doi:10.1080/01621459.2012.722900> and (2015) <doi:10.1007/978-3-319-18732-7_3>. The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems.
Getting started
Browse package contents
Package details |
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| Author | Amandine Pierrot with contributions and/or help from Qiwei Yao, Haeran Cho, Yannig Goude and Tony Aldon. |
| Maintainer | Amandine Pierrot <amandine.m.pierrot@gmail.com> |
| License | LGPL (>= 2.0) |
| Version | 0.1.2.9000 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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